What aspect does a Data Quality Service Level Agreement (DQ SLA) define?

What aspect does a Data Quality Service Level Agreement (DQ SLA) define?

• A. Regulatory compliance for data protection
• B. Roles and responsibilities for data quality procedures
• C. Data storage requirements for customer information
• D. Contractual obligations for data vendors

Answer: (B)

A Data Quality Service Level Agreement (DQ SLA) is designed to outline specific criteria and standards concerning the quality of data. It establishes clear expectations regarding data quality metrics that need to be met, such as accuracy, completeness, consistency, and timeliness. By defining these aspects, it becomes easier to hold all parties accountable for maintaining high-quality data. In this context, the DQ SLA delineates roles and responsibilities related to data quality procedures, ensuring that everyone involved understands their obligations regarding data handling and quality assurance. This clarity helps to foster an environment where data quality is prioritized and systematically managed. The other options do address important areas related to data management, but they do not directly align with what a DQ SLA specifically defines. Regulatory compliance focuses on adherence to legal aspects, data storage requirements pertain to how and where data is stored, and contractual obligations relate to the agreements made with data vendors. While these are essential components of a data governance framework, they do not encapsulate the core purpose of a DQ SLA, which is primarily concerned with data quality and the associated responsibilities.

A Data Quality Service Level Agreement (DQ SLA) is designed to outline specific criteria and standards concerning the quality of data. It establishes clear expectations regarding data quality metrics that need to be met, such as accuracy, completeness, consistency, and timeliness. By defining these aspects, it becomes easier to hold all parties accountable for maintaining high-quality data.

In this context, the DQ SLA delineates roles and responsibilities related to data quality procedures, ensuring that everyone involved understands their obligations regarding data handling and quality assurance. This clarity helps to foster an environment where data quality is prioritized and systematically managed.

The other options do address important areas related to data management, but they do not directly align with what a DQ SLA specifically defines. Regulatory compliance focuses on adherence to legal aspects, data storage requirements pertain to how and where data is stored, and contractual obligations relate to the agreements made with data vendors. While these are essential components of a data governance framework, they do not encapsulate the core purpose of a DQ SLA, which is primarily concerned with data quality and the associated responsibilities.